Remote Household Task Video Recorder

Join our customer's team as a Remote Household Task Video Recorder and make an impact on the future of robotics and machine learning. You will contribute high-quality synchronized motion and video data that powers advanced activity recognition systems—right from your home. This is a unique chance to blend technology and daily activity in a role tailored for detail-oriented, tech-savvy professionals.

Key Responsibilities:

1. Capture synchronized motion data with your smartphone’s IMU sensors while performing specified household tasks.
2. Record high-fidelity video footage alongside sensor data to enhance dataset accuracy and reliability.
3. Follow strict technical protocols to ensure submission quality, precise labeling, and data determinism.
4. Deliver a consistent minimum of 10 hours of approved video data each week, meeting project requirements.
5. Engage proactively with the team to clarify assignment guidelines and share actionable feedback on data processes.
6. Meet deadlines by organizing, preparing, and submitting data in line with project milestones and quality standards.
7. Complete required device compatibility checks and participate in a custom AI-enabled interview process.

Required Skills and Qualifications:

1. Track record of following rigorous protocols and technical procedures in a professional setting.
2. Exceptional written and verbal communication skills, with the ability to document work clearly and collaborate remotely.
3. Strong proficiency in using smartphones and mobile apps for data collection tasks.
4. Physical ability to safely and accurately perform repetitive household movement tasks.
5. Demonstrated commitment to delivering reliable, consistent output in a time-sensitive environment.
6. Access to a compatible smartphone for high-quality IMU and video data capture.
7. Eligibility to work from one of these U.S. states: Alabama, Georgia, Idaho, Indiana, Iowa, Kansas, Kentucky, Louisiana, Mississippi, New Hampshire, North Carolina, North Dakota, Oklahoma, Pennsylvania, South Carolina, Tennessee, Texas, Utah, or Wisconsin.

Preferred Qualifications:

1. Background in robotics, kinesiology, human motion analysis, or sensor-based data collection projects.
2. Experience structuring and labeling large datasets for machine learning applications.
3. Familiarity with activity recognition or activity segmentation protocols.

‍